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penguin-harness/packages/docs/content/models.en.md
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Yaowei Zheng 45bfae6e94 Initialize repository with harness code and assets
Initial import of all source code, config, and README assets: the
packages workspace (cli, core, server, web, docs, landing, skills),
build scripts, tooling config, and CI workflows.

Includes the data-layout revision made on this branch: the local data
root defaults to ~/.penguin/data (PENGUIN_HOME still overrides; the
installer keeps its binaries in ~/.penguin), and every Agent lives
under <project>/agents/<agent>/ — path helpers, the three
agent-enumeration scans, the system prompt, built-in Skills, tests
and docs all follow the new layout.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018ihk8iQuo3kv2aPjAYEPuR
2026-07-19 14:06:53 +08:00

4.5 KiB

title, description
title description
Models & Providers Model access through the single AgentHub gateway, (provider, model_id) identity, the per-Project model table, credentials and thinking levels.

One gateway

All model access goes through one gateway library: @prismshadow/agenthub (AutoLLMClient). Core defines only a thin LLMInterface (see Interfaces); per-provider protocol adaptation happens inside AgentHub, so 1000+ online and local models are reachable, including any OpenAI-compatible endpoint. The protocol translation lives in packages/core/src/llm/generative-model.ts.

Model identity

A model's identity is always the (provider, model_id) pair: provider is a config group name, model_id the upstream request id sent to AgentHub unchanged. The two are independent fields — concatenating them into one string is forbidden anywhere in the pipeline.

The per-Project model table

Each Project's available models are recorded in the hidden .project_config.toml, maintained via the CLI (penguin config model add / default / list, see CLI Reference) or the Web UI — never hand-edited. ModelEntry fields:

Field Meaning
provider Config group name; paired with model_id it forms the unique key
model_id Upstream request id
context_window Context window
client_type Protocol hint (e.g. openai); inferred by AgentHub from the model id when omitted
display_name Display name
vision Whether image input is supported, default true
pricing Three price buckets (unit usd_per_mtok, USD per million tokens): cache_read / cache_write / output
api_key / base_url Inlined credentials, both optional; when blank, AgentHub falls back to environment variables

A fresh Project defaults to deepseek-v4-pro. A vision_model entry can additionally designate the proxy model that describe_image uses for text-only session models (see Tools & Approval); it is unset by default.

File shape (illustrative):

default_model = { provider = "deepseek", model_id = "deepseek-v4-pro" }
vision_model = { provider = "google", model_id = "gemini-3.1-pro-preview" }

[[models]]
provider = "deepseek"
model_id = "deepseek-v4-pro"
context_window = 1000000

[[models]]
provider = "custom"
model_id = "my-model"
client_type = "openai"
base_url = "https://llm.example.com/v1"
api_key = "sk-..."

For a model tagged vision = false (e.g. the DeepSeek series), images from conversation input are saved to the Session scratchpad and handed over as a file path spliced into the text, and the image-reading tool switches to describe_image.

Built-in provider groups

Built-in groups and their env-var fallbacks (catalog source: packages/core/src/state/model-catalog.ts); each group also has a _BASE_URL variant (e.g. ANTHROPIC_BASE_URL):

Provider API key env var Notes
deepseek DEEPSEEK_API_KEY Group of the default model
openrouter OPENAI_API_KEY OpenAI-compatible gateway, preset base URL https://openrouter.ai/api/v1
siliconflow OPENAI_API_KEY OpenAI-compatible gateway, preset base URL https://api.siliconflow.cn/v1
google GEMINI_API_KEY
anthropic ANTHROPIC_API_KEY
openai OPENAI_API_KEY
zhipu ZAI_API_KEY
moonshot MOONSHOT_API_KEY
custom OPENAI_API_KEY Any OpenAI-protocol endpoint

The gateway groups (openrouter / siliconflow) go through AgentHub's OpenAI client, so with blank credentials they read OPENAI_API_KEY — not a gateway-specific variable.

Some models in the preset catalog: deepseek-v4-pro / deepseek-v4-flash, gemini-3.1-pro-preview, claude-opus-4-8 / claude-sonnet-4-6, gpt-5.5, glm-5.2, kimi-k2.6 (not exhaustive).

Thinking levels

Five levels: none | low | medium | high | xhigh, configured per Agent as model.thinking_level in system_config.yaml, default medium. See Configuration.

Models decoupled from Agents

An Agent never binds a model: the model is chosen when a Session is created and stays locked for that Session; the same Agent can run different Sessions on different models. The three pricing buckets feed the usage/cost center's per-Token accounting.

Credential handling:

  • an inline api_key is stored in the hidden Project config file with mode 0600;
  • the Web UI masks it on display;
  • blank credentials fall back to the provider's environment variables.

Connectivity test

The Web Models page offers a per-model connectivity test (owner only).